7 steps to become an AI-enabled enterprise

Finding your artificial intelligence enterprise strategy.

machine learning ai artificial intelligence
Thinkstock

After two decades, platform companies are still collecting tons of data, filling their databases with information of everyone’s knowledge, opinions, recommendations, locations, movements, buying behavior, relation status, lifestyle, etc. This is not a secret and nothing new. And speaking of artificial intelligence (AI), the platform companies are fully embracing and heavily investing into AI. However, most enterprise leaders underestimate the effect this will have on their businesses. And especially the established economy is the big loser in this game. Read this article to get a better understanding of the powerful forces that are happening right now and why you need a general AI strategy to run your IT operations and other business processes autonomously.

Challenges for the established economy

Nowadays, there are multiple challenges established companies are faced with. This is the often-quoted war for talent or the inability of many large corporates to change effectively. But there is an underestimated threat called competition as well – not from their own peers – but from high-tech companies that are unstoppably marching into their markets. These so-called platform companies – speaking of Google, Amazon, Facebook, Alibaba, Baidu, Tencent, etc. – invade the well-known competitive space of established companies with unimaginable financial resources and by hijacking the consumer lifecycle. As a result, established companies have to find powerful answers, if they want to exist tomorrow. These are three main threats for the established economy – ensuing from platform companies:

1. The ability to "burn" money

Platform companies do have more financial resources they can leverage to invest with no urgency to prioritize budgets. They simply use more money to experiment. In contrast, companies from the old economy have very little money to invest or to play with since they are constantly subject to pressure through their external stakeholders like capital market, shareholders, customers, etc.

As an example, imagine the pharmacy giants Fizer from the U.S. or Bayer from Germany develop a drug to solve cancer and imagine they invest USD 500 Mio. into this adventure. Well, this project has to work. Otherwise, the CEO of each company will be fired on the same day he announces that the project failed and the company stock will go down at least by 30 percent. Why? Because it is the core business of Pfizer as well as Bayer to develop drugs. So, every dollar they invest into research and development has a direct impact on their core business.

Now, let’s imagine a platform company like Google or Alibaba doing exactly the same thing. Developing a drug to solve cancer with a project volume of USD 500 Mio. What happens if this does not work? Well, this is a different story. Jack Ma of Alibaba would simply get in front of financial analysts and other stakeholders and would say something like, “We tried to solve cancer. We failed. We burned USD 500 million. But, we will learn from our mistakes and we will try again!” Ma would be considered a hero since Alibaba’s very core business is not being a pharma company but a web-shop selling goods. And Alibaba “sacrificed” budget to find a solution against cancer. And in addition, this type of mistake does not have a direct impact on the core business. It’s the same with Google (Internet search and advertisement – 98 percent of Alphabet’s revenue comes from advertisements) or Amazon (web shop).

However, it is one thing to have access to money, but another even more important thing is to have the mindset. Platform companies do have the ability and the mindset to take risks and “burn” money. Something, companies from the old economy do not have. Just take Amazon’s Jeff Bezos as the prime example. Instead of satisfying the shareholders with dividends, Bezos consequently reinvests the biggest part of the revenue into research and development (USD $16.1 billion in 2016) and lets Amazon experiment. Bayer, on the contrary, just spent USD $5.2 billion in 2016 for R&D.

2. The strategy to hijack direct customer relationships

Platform companies hijack the direct relationship between the established companies and their customers. In the past, a brand established its direct customer relationships by offering products and services on multiple channels via retail, customized advertising or e-commerce. Using these platforms, brands influenced customers to buy their products and services. However, customers chose the platform of their choice to buy goods and services via the various platform (channels).

Today, the point of sale moves into the platforms of companies like Google, Amazon, Alibaba or Facebook. And that’s because any social media consultant advises to use Facebook to engage with customers, advertise via Google or sell goods through Amazon or Alibaba. Looking at this advice from one angle, it is indeed true. Because these platforms empower you to reach a broader audience in all cases. However, looking at it from another angle, social media advisors are false friends. Why? When you decide to move your marketing and sales operations to a platform company you immediately lose the direct customer relationship. You may get analytics and some data from Facebook, Google, Amazon and co. but you are losing the direct connection to your customer. As a consequence, a customer (possibly your existing customer) is engaged with an AI assistant platform. You might think, “So what?!” However, in an interview with “The Drum,” Alibaba’s principal engineer Rong Jin explained that “AI technology will also enable Alibaba to enhance product recommendations and help identify the most effective stages of the process to target consumers to influence their final purchasing decisions.” And that “Alibaba is using artificial intelligence (AI) to create tailor-made shopping experiences for consumers and targeted marketing for brands as it seeks to empower people in the virtual economy.” Jin also mentioned that “AI technology will transform Alibaba’s business in the future by enabling the company to connect the data generated across the company’s ecosystem to better understand its consumers and better optimize the shopping process for them.”

Thus, a platform (leveraging AI technologies) will always satisfy the customers to keep them from switching. So, the platform (the AI technology) chooses goods and services from a pool of brands based on the customers’ preferences. Good for the platform, alarming for companies from the old economy.

3. The power to collect massive data for building general AI

Platform companies collect endless amounts of data and thus create their own general AIs. A general AI can handle tasks from different areas and origins. It applies experience from one area to another and thus learns faster. However, knowledge transfer is only possible if there is a semantic connection between different areas. And the stronger this connection, the faster knowledge transition is achieved.

In order to build general AIs, they follow the quid pro quo principle. End consumers give their data/ knowledge to the platform companies and in return get free access to offered services. Virtual private assistants like Amazon Echo or Google Home are the next evolutionary step, which can be used to control smart home devices or make our lives easier by simply using our voice. This simply shows that Amazon, Google and co. find new ways to engage with us over other channels, collecting the data, information and knowledge they need to make better decisions and to deliver better answers back to us. Therefore, they clearly follow one purpose. Every one of us is simply being used to train their AI on a daily basis. Meaning, all the services Google and co. offer to their customers are aimed at creating general AIs with the data they get.

Talking with “The Drum,” Rong Jin explained that Alibaba’s “[…] data analysis and data pattern mapping will also help inform data models that Alibaba can apply to other sectors, beyond ecommerce. Alibaba has begun using AI technology to upgrade business sectors such as finance, shipping, healthcare and entertainment.” And this is nothing else but creating a general AI.

However, the general AIs from the platform companies are used to build disruptive or disintermediating approaches that cannot be used by enterprises from the old economy who are threatened by these disruptions and intermediations.

AI is the strongest tool to overcome the threats

A strong brand, outstanding services and innovation are the conditions for survival. But turning exponential is the only way to successfully compete against companies that are already exponential. In addition, platform companies think big regarding their targets for improvement. They choose to start disrupting industries that touch billions such as healthcare, transportation, communications, energy, finance and telecoms.

AI is one of the tools – potentially the only one – in the corporate toolkit to help overcome these competitive threats and make use of the strong side of established companies: their experience. Building an own general AI, established companies can run any process autonomously across their organization while retaining their knowledge and monetizing their data and experience. However, the established economy needs an own independent platform approach since each one of them has too narrow data to build a general AI on their own. They need someone to organize their data, allow security control on details and publish aggregates. They need to have access to an AI platform to multiply their IP and experience. Their AI needs a full data pool, but their individual data, IP and experience needs to stay under their control. In the following, established companies find a step by step strategy they can take to execute the idea:

  1. Established companies collect every piece of data within the company.
  2. Give data to a secure and independent intermediary platform operating a shared data pool for established economy.
  3. In return, they get access to a shared pool of aggregated and semantically organized data.
  4. They use this data and the necessary technology to build their own corporate general AI.
  5. Outcome based on corporate general AI: New business models, offerings, services etc.
  6. Give resulting data from new business models, offerings, services etc. to the shared data pool.

Adapting this approach, established companies are enabled to run an AI and make use of their knowledge and data. They keep their intellectual property and create value from their experience.

AI-enabled enterprise: anything that is a process can be and will be run by an AI

Today with AI, anything that is a process can be automated. Meaning, introducing an AI immediately leads to higher automation rates that results in saving costs and more time for talented people who can shift their focus on strategic things. Ergo, leveraging AI leads to more money and time and thus the ability to innovate. So, on your journey to new business models, imagine what you can do with the financial resources and talent set free when today’s business is largely run by AI. The following seven steps help your company to become an “AI-enabled enterprise”:

  1. Create a semantic map of your data: accept continuous data flow as a foundation for future strategy.
  2. Automate your IT operations and make them autonomous: automate IT operations to receive immediate value brought by AI and collect data.
  3. Rethink your strategy: think about a new (exponential) business model.
  4. Retrain your entire organization top-down: prepare and train your organization for an AI-enabled enterprise and accepting a new business model.
  5. Expand autonomous operations to other business processes: using company knowledge gathered through IT automation and make more processes autonomous.
  6. Embrace predictive analytics: use data from the semantic map to expedite, improve business processes and future business events.
  7. Consider data-driven processes: Use data and AI to generate outcome-based processes.

However, all data that exist will be collected in the entire company and will eventually end up in the IT environment: stored in applications, databases or storage systems. Thus, it is recommended to start setting up an AI in IT environments, because IT is at the core of any company and all relevant information passes through this area. IT generates a fantastically regular continuous data set which can be used as a statistical foundation for semantic mapping. And over time a company can derive any learning about its organization and market, both based on the IT that is at the very core of the company.

Most importantly, come out of your comfort zone – your existing business and industry you operate in right now. It doesn’t help you to simply develop something for the media industry when you are a media company. You have to think across industries and develop something that adds an additional value for your customers and thus opens a new industry for you.

Hint: Amazon was only a web shop some years ago. Now, it has multiple business units and is still growing through experiments and just tries if something works.

This article is published as part of the IDG Contributor Network. Want to Join?

NEW! Download the Winter 2018 digital edition of CIO magazine